Abstract:  [Objective] The characteristics of the in-situ stress field are key fundamental parameters for major strategic underground engineering projects, deep earth resource and energy development, and geohazard prevention and control. Over the past decade, significant progress and breakthroughs have been made in in-situ stress measurement and estimation methods. [Method] This article systematically reviews the main advances in in-situ stress measurement and estimation methods from 2014 to 2025, which can be categorized into four technical fields: core-based methods, borehole-based methods, geophysics-based methods, and emerging data-driven estimation methods. [Results] Core-based testing methods have improved the accuracy of in-situ stress magnitude measurements through theoretical refinements and enhanced the precision of stress direction determination through equipment upgrades, addressing the previous inability to measure in-situ stress in low-strength rocks. Borehole-based testing methods have achieved sensors with high temperature and pressure resistance, as well as corrosion resistance, enabling deep borehole imaging, direction identification, and in-situ stress measurement. Accurate analytical solutions for in-situ stress magnitudes have been obtained through corrections. Geophysics-based methods have enabled the inversion of the in-situ stress field using focal mechanism solutions of minor earthquakes (magnitude 0.5–1.0), providing extensive rock mass stress information. Acoustic, imaging, and dipmeter logging technologies have also evolved into non-contact, high-precision, and high-sensitivity equipment, making them more suitable for deep boreholes and oilfield development. With the advancement of big data and artificial intelligence, emerging data-driven testing methods can be divided into three categories based on prediction approaches: machine learning, intelligent neural network prediction, and intelligent back-analysis. These methods have advanced in-situ stress measurement from discrete "point measurements" to full-field "field reconstruction." [Conclusion]Compared to traditional methods, current in-situ stress testing is moving toward "deepening, intelligentization, and systematization." [Significance]Future research should focus on the dual drivers of intelligent prediction models and intelligent testing equipment to address the challenges of complex deep geological environments.